MétaCan
Menu
Back to cohort
Record W4390078775 · doi:10.1017/s1355617723002795

76 The Effects of Strategies-Based Training in Improving Memory Outcomes in Healthy Older Adults

2023· article· en· W4390078775 on OpenAlexaboutno aff
Bianca E Tolan, Richelin V. Dye

Bibliographic record

VenueJournal of the International Neuropsychological Society · 2023
Typearticle
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMnemonicVisual memoryIntervention (counseling)PsychologyCognitionMedicineMontreal Cognitive AssessmentClinical psychologyAudiologyGerontologyCognitive impairmentPsychiatry

Abstract

fetched live from OpenAlex

Objective: The goal of our study was to examine the possible effects of a strategies-based training intervention on objective memory performance and subjective memory in healthy older adults. While slight declines in memory naturally occur in the aging process, these changes may impact the quality of life for older adults. Participants and Methods: Patients (n = 11, aged 50-80, mean age = 70.73, SD = 4.41) with subjective memory complaints were recruited from memory clinics within an academic medical center. All participants engaged in one-on-one, three one-hour memory training sessions over the course of several weeks to undergo strategies-based training intervention (e.g., mnemonics). All participants completed neuropsychological battery of tests at baseline and at post-intervention (about 8-10 weeks after baseline). Tests included the Montreal Cognitive Assessment (MoCA), the Hopkins Verbal List Test (HVLT-R), the Visual Reproduction subtest of the Weschler Memory Scale (WMS-IV), and the Multiphasic Memory Questionnaire. Results: Data were analyzed using a mixed between-within subjects ANOVA and t-tests. Groups were created based on the participant’s MoCA score. While a total of 11 participants completed baseline testing and the memory training sessions, two did not return for post-intervention testing; as such their data were excluded from analyses. Older adults with a MoCA score of 26-30 (n = 6), but not older adults with a MoCA score 25 and below (n = 3), had a significant improvement in visual learning and encoding, F (1, 7) = 10.028, r = .50, p < .05. The high MoCA performers demonstrated an improved performance in their immediate visual memory from baseline (M = 10, SD = 3.53) to post-intervention (M = 12, SD = 3.35), t(9) = .895, p = .001 (two-tailed). Ratings of memory satisfaction among high MoCA performers also increased from baseline (M = 48, SD = 11.47) to post-intervention (M = 51, SD = 5.43), t(9) = .707, p < .05 (two-tailed). Among both groups, a significant increase in perceived memory ability was demonstrated from baseline (M = 50, SD =10.1) to post-intervention (M = 54, SD = 12.35), t(8) = .807, p < .05 (two-tailed). Conclusions: These findings indicate that a brief memory training program may improve visual encoding and subjective memory in healthy older adults with memory concerns. Individuals with subjective memory concerns who undergo a cognitive training program seem to demonstrate improved encoding of nonverbal material. These participants also reported a greater memory satisfaction and improved perceived memory ability after completion of a memory training program. Interestingly, these findings were only seen in adults whose MoCA performance was within normal limits. Although a systematic review suggests the improvement of memory performances on cognitively impaired participants (Simon, Yokomizo, & Bottino, 2012), this may not have been demonstrated in the current study due to a low sample size and/or to the brief duration of the cognitive training. Future directions include increasing sample size and offering booster sessions to explore whether cognitively impaired adults may benefit from repetition.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.363
Teacher spread0.334 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the International Neuropsychological SocietySame topicHealth and Well-being StudiesFrench-language works237,207